Data communication detectors are used in read channels of disc drives. State of the art detectors employ Data-Dependent Noise Whitening (DDNW) metrics, either in the branch metrics of a Viterbi detector, or in a post-processor that effectively ‘corrects’ decisions made by a non-DDNW metric Viterbi. The data-dependent noise whitening process is accomplished with a finite-impulse response (FIR) discrete time filter, implemented in hardware as a transversal filter structure.
The required data-dependent transversal filter coefficients for noise whitening are estimated or adapted using a Least Means Squared (LMS) algorithm. The LMS algorithm used with a transversal filter structure, however, has slow filter convergence, especially when the filter input correlation matrix has a large eigenvalue spread, such as occurs with high density magnetic recording. In addition, a digital transversal filter implementation requires a priori fixed range and resolution of the data-dependent coefficients for finite precision representation. However, since each transversal filter coefficient must be allowed to take a different value for each data pattern considered, there is in practice no way to know beforehand how to optimally choose finite precision range and resolution for this structure.
The transversal structure also does not allow for efficient order-decoupling or modularity. In other words, if the optimal Lth order whitening transversal filter has been calculated, one must re-calculate the values of all filter coefficients in order to achieve the optimal (L+1)th order filter. Each time the order of the filter changes, there is a requirement to recalculate the values of all filter coefficients. The transversal filters are not modular filters.
A noise whitening filter structure is needed that provides efficient whitening of data-dependent noise for the purpose of data detection over inter-symbol interference channels without suffering the disadvantages inherent in the transversal structure. Embodiments of the present invention provide solutions to these and other problems, and offer other advantages over the prior art.